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LensVLM-9B-MXFP4

sahilchachra

基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。

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TeleOCR-MXFP8

sahilchachra

基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。

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Unlimited-OCR-AWQ

sahilchachra

AWQ 4-bit (W4A16) quantization of **baidu/Unlimited-OCR**, a 3B vision-language OCR model that pushes **DeepSeek-OCR** one step further (one-shot, long-horizon document parsing). This repo quantizes the **DeepSeek-V2 MoE text decoder** with activation-aware scaling (AWQ) while keeping the vision tower in BF16, so it stays a drop-in `transformers` model. > ⚠️ **Runtime requirements.** This is custom remote code, so load with > **`trust_remote_code=True`**, **`transformers` 4.57.x**, and **`compressed-tensors`** installed. > W4A16 (int4) runs on any CUDA GPU; `compressed-tensors` handles the 4-bit unpacking at load. Unlimited-OCR uses the **DeepSeek-OCR** prompt vocabulary. The prompt **must contain ` `**; prefix it with ` ` whenever you also want **bounding boxes** for what was read.

Text generationOpen weights
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Unlimited-OCR-GGUF

sahilchachra

GGUF quantizations of **baidu/Unlimited-OCR**, a 3B vision-language OCR model that pushes **DeepSeek-OCR** one step further (one-shot, long-horizon document parsing). This repo contains a full spread of **K-quants and i-quants** of the language model plus the **vision projector (mmproj)** needed for image input. > ⚠️ **Requires a DeepSeek-OCR–aware llama.cpp build (PR #17400).** > Unlimited-OCR uses the DeepSeek-OCR architecture (a SAM+CLIP *DeepEncoder* vision tower > with a DeepSeek-V2 MoE text decoder). Support is **not yet merged into upstream `main`** — > stock llama.cpp will not load these files. Build the PR branch (instructions below). Every run needs **two** files: one language model GGUF (pick a quant) **plus** the shared vision projector. The projector is fp16 and identical for all quants.

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